Systematic Equities Quantitative Researcher

Anson McCade

Hong Kong

On-site

HKD 1,200,000 - 1,900,000

Full time

29 hours ago
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Job summary

Anson McCade is supporting a market-leading proprietary trading and market making firm in APAC, seeking a Systematic Equities Quantitative Researcher to grow its cash equities program.

You will own the research-to-live-trading pipeline, develop alpha signals, backtest strategies robustly, and work with traders and engineers to improve execution, with strong autonomy and end-to-end ownership.

Qualifications

  • 4+ years of experience in quantitative research or systematic trading.
  • Strong programming skills in Python; C++ knowledge is a plus.
  • Experience with machine learning techniques and bringing research to live trading.

Responsibilities

  • Conduct quantitative research to identify systematic trading opportunities in cash equities.
  • Generate, test and refine alpha signals and predictive models.
  • Design robust backtests and evaluate strategy performance.
  • Develop and optimise trading strategies for live deployment.
  • Collaborate with traders, researchers and engineers to improve execution.

Skills

Python
Machine learning
Quantitative research
Autonomy
End-to-end ownership

Education

Quantitative degree (Math/CS/Physics)

Tools

C++

Job description

My client is a market-leading proprietary trading and market making firm that is continuing to expand its quantitative trading capabilities across APAC. As part of this growth, the firm is looking to hire an experienced Systematic Equities Quantitative Researcher to help build and develop its systematic cash equities business.

This is an opportunity to join a highly successful global trading firm while taking on significantly greater autonomy, ownership and end-to-end responsibility for research and strategy development. You will work across the full quantitative research and trading pipeline, with the opportunity to take ideas from initial research through to implementation and live trading.

Responsibilities will include:

  • Conducting quantitative research to identify and develop systematic trading opportunities in cash equities.
  • Generating, testing and refining alpha signals and predictive models.
  • Designing and running robust backtests and evaluating strategy performance.
  • Developing and optimising trading strategies for live deployment.
  • Working closely with traders, researchers and engineers to improve execution and overall strategy performance.
  • Exploring and applying machine learning techniques where appropriate to enhance research and modelling capabilities.

The ideal candidate will have:

  • 4+ years of experience in quantitative research or systematic trading.
  • A strong background in HFT or MFT systematic cash equities strategies.
  • Experience working at a leading hedge fund, proprietary trading firm, market maker or other top-tier buy-side trading environment.
  • Demonstrable experience taking research ideas through the full lifecycle, from data analysis and signal generation through to backtesting, implementation and live trading.
  • Strong programming skills, ideally in Python, with additional experience in C++ or other languages beneficial.
  • A strong academic background, ideally from a leading university in a quantitative discipline such as Mathematics, Statistics, Computer Science, Physics, Engineering or a related field.
  • Experience with machine learning techniques would be highly advantageous.

You will benefit from:

  • Greater autonomy and influence over your research and strategy development.
  • End-to-end ownership, with the ability to take ideas from initial concept through to live trading.
  • The opportunity to build and own strategies rather than focusing on a narrow part of the research pipeline.
  • A highly collaborative environment, working alongside experienced researchers, traders and technologists.
  • Access to a market-leading trading and technology platform.
  • The opportunity to join a rapidly expanding APAC business with significant scope for growth and long-term impact.
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